Month: January 2021

Crisis Plan—Evaluation and Analysis

Academic level        Undergraduate. (Yrs. 3-4)

Type of paper          Other

Discipline      Social Work and Human Services

Pages 4

Responding Organizations

Academic level        Undergraduate. (Yrs. 3-4)

Type of paper          Other

Discipline      Social Work and Human Services

Pages 3

Solar Energy Expansion in Greece

Academic level        PhD

Type of paper          Research paper

Discipline      Management

Pages 30

CASE STUDY: A Foodborne Outbreak Among Inmates at a County Jail

Academic level        Undergrad. (yrs 3-4)

Type of paper          Essay (any type)

Discipline      Biology (and other Life Sciences)

Pages 2

 

Crisis-response organizations

Work type:   Discussion Essay

Format:         APA

Pages:            2 pages ( 550 words, Double spaced

Academic level:       Undergrad. (yrs 3-4)

Subject or discipline:         Social Work and Human Services

Title:   Before a Crisis

Number of sources:           3

Paper instructions:

Post a brief description of the three crisis-response organizations you selected. Then describe the roles of each organization as well as the relationships between and among them.

Please use these resources

James, R. K. & Gilliland, B.E. (2017). Crisis intervention strategies (8th ed.). Boston, MA: Cengage Learning.

• Chapter 5, “Crisis Case Handling” (for review)
• Chapter 17, “Disaster Response”

Crisis Management in the New Strategy Landscape

• Chapter 4, “A Strategic Approach to Crisis Management”
• Chapter 5, “Forming the Crisis Management Team and Writing the Plan”

• Appendix, “Sample Outline of

Crisis plan in Mississippi Hurricane Katrina

Work type:   Discussion Essay

Format:         APA

Pages:            2 pages ( 550 words, Double spaced

Academic level:       Undergrad. (yrs 3-4)

Subject or discipline:         Social Work and Human Services

Title:   During a Crisis

Number of sources:           4

Paper instructions:

using Hurricane Katrina as your natural disaster example, a description of at least one strength and one limitation of the crisis plan developed by the state of Mississippi. Explain what you would do to improve the limitation you described.

Please use these resources

Governor’s Commission on Recovery, Rebuilding, and Renewal. (2005). After Katrina: Building back better than ever. Retrieved from http://www.mississippirenewal.com/documents/Governors_Commission_Report.pdf

Shah, A. (2005). Hurricane Katrina. Retrieved from http://www.globalissues.org/article/564/hurricane-katrina

The Mississippi Renewal Forum. (2005). Summary report. Retrieved from http://mississippirenewal.com/documents/Rep_SummaryReport.pdf

Holdeman, E. (2012). Hurricane Katrina and the Lessons Learned from Mississippi’s Recovery. Retrieved, January 2, 2016 from http://www.emergencymgmt.com/disaster/Hurricane-Katrina-Lessons-Learned-Mississippis-Recovery.html?page=3

Wolshon, B. (2006). Evacuation Planning and Engineering for Hurricane Katrina https://www.nae.edu/Publications/Bridge/TheAftermathofKatrina/EvacuationPlanningandEngineeringforHurricaneKatrina.aspx

Personalization is key in telecommunications. And analytics the natural solution.

Telenor Norway uses SAS Analytics to enhance business decisions and continuously adapt to customers’ needs

For Telenor Norway, the customer is at the center of everything it does. Being relevant to clients and being able to adapt products according to customer expectations is more important than ever. Personalization is key. And analytics the natural solution.

“For Telenor, personalization means to be relevant for the customer,” says Liv Elise Saue Tøftum, Director of Analytics and Customer Lifecycle Management at Telenor. “It is about meeting the customer with the right message, at the right time, in the preferred channel. To reach this level of personalization, everything we do and don’t do needs to be based on insight.”

In 2010, Telenor sent its first personalized SMS to customers. And over the last decade, the company has expanded the reach and relevance of its customized messages. Telenor has experienced a 40% to 50% growth of personalized upsales in the last two years. Now 40% of all sales are personalized, and 95% of customer interactions are digitized.

Over the course of one year, Telenor sent 50 million personalized next best offers to its customers. They were generated by Telenor’s guidance tool, Automated Sales Tips (AST), which was built with SAS.

The right use of data can lead to new sales

However, as easy it may seem, being relevant for the customer can be difficult. “Personalized actives can trigger sales but also trigger churn,” Tøftum says. “An SMS to a customer who does not want to be contacted can, in the worst case, be the trigger for that customer to discontinue his or her subscription.”

 

Tøftum believes there are three key steps organizations need to take to stay relevant:

• Collect and analyze the right data.
• Act on insights from the data.
• Execute, follow up and iterate.

Telenor Yng, Telenor’s new subscription for young adults, is a great example of how data has informed a major rebranding in the youth segment. Using internal and external data and advanced analytics from SAS, combined with a process connecting the business and science sides, Telenor Yng achieved impressive results. After four months, Telenor Yng attained 80% customer awareness. In comparison, its former youth subscription, Djuice, had 78% customer awareness after 17 years in the market. Additionally, the churn in the youth segment reduced 8 percentage points.

It is about meeting the customer with the right message, at the right time, in the preferred channel. To reach this level of personalization, everything we do and don’t do needs to be based on insight.

Liv Elise Saue Tøftum Director of Analytics and Customer Lifecycle Management Telenor Norway

Investing in analytics pays off

Telenor is continuously adapting to customers’ needs. To do that, it works systematically to nurture and mine its data while applying the latest advanced analytics.

“We have developed advanced analytics and predicative models and built a solid reporting structure based on self-service with SAS Viya across the organization,” Tøftum says. “And we have systemized and automated our activities based on contextual triggers.”

Going forward, Telenor will continue to work with an efficient and seamless customer journey across all touch points, with next best offers implemented across the channels.

“Now we are building our big data platform with the newest SAS Viya tools on top, and we have great expectations to what we are going to achieve in business value,” Tøftum says.

Integrating business with data science

According to Tøftum, the biggest challenge with new technology is integrating the technology into the organization. But that also leads to the biggest gain.

“It is when you understand how you can interpret the data – and how the business side works with the data science side – that you get real business value,” Tøftum says. “And that’s why we partnered with SAS.”

 

Building a bank that can surprise and delight with Power Business Intelligence – BI

When Metro Bank opened in London in 2010, it was a brash competitor in a seriously traditional industry. The vision? To redefine the relationship people have with their bank by innovating customer service. With such offerings as seven-day-a-week store hours and lightning-quick service — a customer can open an account and get a debit card within minutes — the bank built a foundation for fast growth, doubling in size year after year and soaring to more than 500,000 customer accounts.

But with that growth has come a need for deeper and more detailed information about what customers want and need — how they interact with the bank’s services, including stores, online, telephony and mobile. Metro Bank needed a business intelligence (BI) solution that could quickly and accurately provide information to guide analysis and decision-making. Microsoft Power BI gave Metro Bank what it was looking for, with interest.

A focus on customers

“We set out to create fans, not customers,” says Bruce Rioch, Director, Microsoft Technologies & BI at Metro Bank. “We want to surprise and delight. We want to be the bank that our customers tell their family and friends about — the bank that offers amazing customer service and has a simple, understandable proposition.”

To provide an innovative, personalized service, Metro Bank needs to capture rich detail about its customers, from how long it takes to resolve their questions via telephone call centers, to identifying peak times for transactions conducted via the bank’s mobile app. And those details need to be clear and easy to understand, and available to the right person at the right time.

“As we’ve grown, more and more people have been asking questions about how effective or efficient the service is, and how well we are providing services,” Rioch says. “We struggled along during the first few years; we had what we needed. But as we’ve grown bigger, the question has become ‘how on earth do we provide the right information to the right people at the right time?’

A system that looks familiar

Metro Bank decided to implement Microsoft Power BI because the solution integrated easily with the bank’s existing Microsoft stack, and was easy for colleagues to quickly learn and personalize for their daily needs.

 

“Power BI is our only BI solution,” Rioch says. “We had a solution previously that was fine for us as a brand-new startup organization. But as we grew, we needed something more dynamic, more visually appealing and more user-friendly for our colleagues. Power BI fits the bill in all of those respects.”

Metro Bank uses Power BI to track customer interactions, internal metrics and more.

Call center operations. Power BI enables Metro Bank to track call volume, service levels, customer demographics, call times and shift scheduling. Reporting data is refreshed each night so colleagues have a clear picture of the previous day, weeks, months or year.

Mobile and Internet banking. Colleagues can analyze data including the volume and types of transactions customers are performing online, the devices they use, and peak activity times throughout the day. “We get a real sense of how the channels are growing, and how they’re being used by our customers, and what services they use once they’re inside that service,” Rioch says. “Which is quite important because it helps us direct what we build next.”

Customer dissatisfaction reports. Metro Bank can track customer complaints, including the rate of open complaints per 1,000 accounts, the time it takes to resolve them and the departments involved. One key feature is the ability to flag the most urgent complaints so that colleagues can take steps to resolve them before the deadline for reporting an outstanding issue to regulatory bodies.

Staffing and workload planning. Power BI collects data on peak activity times in bank branches, types of transactions and other customer activity details, enabling Metro Bank to plan staffing to meet customer demands — for example, identifying the busiest hour of the busiest day of the month per branch — and help ensure quick, efficient service.

Rich detail, easy to visualize

By collecting rich detail and making it easy to analyze through personalized dashboards, Power BI helps bank colleagues identify problems before they can affect the bank’s relationship with the customer. Colleagues can combine details from account activity, data from customer satisfaction surveys, branch traffic patterns and more to understand which proactive solutions can make the biggest difference to the customer experience. Similar survey data offers insight into the employee experience, or what Rioch calls “the voice of the colleague.”

“The internal survey is built out of the dashboard,” Rioch says. “In the past it would have been all spreadsheet-driven; this year we’ve been able to display the colleague results really visually — and fantastically.”

As a participant in the Power BI Preview, Metro Bank is also working with Microsoft developers to preview and test new features and offer feedback on functionality. The bank’s input helps shape the future of Power BI. And the dynamic program provides frequent updates, helping Metro Bank continually improve its customer service and offerings built on new capabilities.

“We use Power BI for everything,” Rioch says. “We love this product.”

Survivor and Responder Disaster Responses

Work type: Discussion Essay

Format:      APA

Pages:         2 pages ( 550 words, Double spaced

Academic level:   Undergrad. (yrs 3-4)

Subject or discipline:    Social Work and Human Services

Title: Survivor and Responder Disaster Responses

Number of sources:      4

 

Post an analysis of implications of vicarious trauma, burnout, and compassion fatigue for counselors and first responders. Please address all four areas

Please use these resources and your choice

American Counseling Association (ACA). (2005). 2005 ACA code of ethics [White Paper].           Retrieved from     http://www.counseling.org/docs/ethics/aca_2005_ethical_code.pdf?sfvrsn=2

James, R. K. & Gilliland, B.E. (2013). Crisis intervention strategies (7th ed.). Belmont, CA:           Thomson Brooks/Cole. ISBN: 978-1-111-18677-7.

• Chapter 16, “Human Services in Crisis: Burnout, Vicarious Traumatization, and Compassion Fatigue”

 

Pross, C. (2006). Burnout, vicarious traumatization and its prevention. Torture Volume 16,           Number 1, 2006. Retrieved, January 14, 2016 from           http://www.irct.org/Files/Filer/TortureJournal/16_1_2006/page_1-9.pdf

Trippany, R. L., White Kress, V. E., & Wilcoxon, S. A. (2004). Preventing vicarious trauma:           What counselors should know when working with trauma survivors. Journal of           Counseling and Development, 82 (1), 31-37. Retrieved from the Walden Library           databases.

 

 

 

Business Intelligence case study

The purpose of the essay is to demonstrate an understanding of key principles of Business Intelligence and its business benefits and issues, as well as apply relevant theories and frameworks to understand BI in practice.

Task break-down

1. The two case studies are;

https://customers.microsoft.com/en-us/story/building-a-bank-that-can-surprise-and-delight-with-pow

https://www.sas.com/en_is/customers/telenor-personalization.html

2. Apply the DIKAR model for both case studies separately to analyse the BI implementation. For each case study you need to clearly show:

What were the planned business Results (note that ‘having a BI system’ is not a business need – you need to look at what the organisation thinks what business purpose it needs the BI system for), Actions, necessary Knowledge, Information, Data? (RAKID)

• What data was used in reality, what information and knowledge generated, what actions supported and what were actual business results? (DIKAR)

3. Using appropriate models, frameworks and theories, for both case studies, analyse how BI was implemented, paying attention to both the technology used and organisational/managerial elements. Note that an analysis is required here, not simply a description.
4. Compare and contrast the cases – what relevant similarities and differences can you identify, and how does this align with theoretical frameworks?
5. Based on your findings for questions 2-4, draw conclusions on the implementation of BI. Make sure you reflect on any potential bias in the case studies.

1)    Use of academic sources

• Use of sufficient and appropriate academic sources, including the textbook
• Application, rather than description, of academic theories/models/frameworks 2)

2)    Analysis

• Cases analysed well: critical analysis (including using DIKAR) rather than description
• Good comparison of the cases
• Demonstrating good knowledge and understanding of BI
• Clear, logical structure

3)    Conclusions

• Clear conclusions that follow logically from the analysis

4)    Overall Presentation (

• Layout and clarity
• Correct referencing

NOTES:

There is no need to analyse data. What you need to analyse is text in an academic sense. show that you understand the relationship between business needs and the use of BI, as well as showing awareness of challenges involved in implementing BI in an organisation.

It should be clear that using IT analytical tools isn’t going to get you there. You need to use academic frameworks/theories, in particular DIKAR for your analysis.

2000 words , maybe you can do 100 for introduction , 600 for each Case study , 500 for comparison and 200 for conclusion   a